Related papers: Automated Atomic Silicon Quantum Dot Circuit Desig…
Quantum kernels hold great promise for offering computational advantages over classical learners, with the effectiveness of these kernels closely tied to the design of the quantum feature map. However, the challenge of designing effective…
Advances in quantum technologies are often limited by slow device characterization, complex tuning requirements, and scalability challenges. Spin qubits in electrostatically defined quantum dots provide a promising platform but are not…
Within the familiar circuit-based quantum computational setting, we introduce and analyze a toy model of a quantum physical device capable of internal, self-referential deliberation. The key idea is to represent ``deliberation'' as a…
This paper proposes a robust control design method using reinforcement-learning for controlling partially-unknown dynamical systems under uncertain conditions. The method extends the optimal reinforcement-learning algorithm with a new…
In the emerging field of Fault Tolerant Quantum Computation (FTQC), resource estimation is an important tool for quantitatively comparing prospective architectures, identifying hardware bottlenecks and informing which research paths are…
In the last decades, great achievements have been made in the development of computing machines. However, due to exponential growth of transistor density and in particular due to tremendously increasing power consumption, researchers expect…
As the number of qubits in a sensor increases, the complexity of designing and controlling the quantum circuits grows exponentially. Manually optimizing these circuits becomes infeasible. Optimizing entanglement distribution in large-scale…
Quantum Architecture Search (QAS) is an emerging field aimed at automating the design of quantum circuits for optimal performance. This paper introduces a novel QAS framework employing hybrid quantum reinforcement learning with quantum…
Scalable quantum technologies will present challenges for characterizing and tuning quantum devices. This is a time-consuming activity, and as the size of quantum systems increases, this task will become intractable without the aid of…
Electron spin qubits in quantum dot devices are promising for scalable quantum computing. However, architectural support is currently hindered by the lack of realistic and performant simulation methods for real devices. Physics-based tools…
Recent developments in quantum hardware indicate that systems featuring more than 50 physical qubits are within reach. At this scale, classical simulation will no longer be feasible and there is a possibility that such quantum devices may…
Emerging reinforcement learning techniques using deep neural networks have shown great promise in control optimization. They harness non-local regularities of noisy control trajectories and facilitate transfer learning between tasks. To…
Interacting spin systems in solids underpin a wide range of quantum technologies, from quantum sensors and single-photon sources to spin-defect-based quantum registers and processors. We develop a quantum-computer-aided framework for…
Recent advances in quantum error correction (QEC) codes for fault-tolerant quantum computing \cite{Terhal2015} and physical realizations of high-fidelity qubits in a broad range of platforms \cite{Kok2007, Brown2011, Barends2014,…
The rapid development of quantum dot (QD) devices for quantum computing has necessitated more efficient and automated methods for device characterization and tuning. This work demonstrates the feasibility and advantages of applying…
Automated processor design, which can significantly reduce human efforts and accelerate design cycles, has received considerable attention. While recent advancements have automatically designed single-cycle processors that execute one…
Coherence and scalability are essential properties of quantum systems required in quantum computers. This study presents a high coherent and scalable qubit system with atomtronics in synthetic dimensions. It is atomtronic counterpart of…
Gate-defined semiconductor quantum dot (QD) arrays are a promising platform for quantum computing. However, presently, the large configuration spaces and inherent noise make tuning of QD devices a nontrivial task and with the increasing…
Quantum computers based on cold-atom arrays offer long-lived qubits with programmable connectivity, yet their progress toward fault-tolerant operation is limited by the relatively low fidelity of site-selective local control. We introduce…
Gate-defined quantum dots (QDs) have appealing attributes as a quantum computing platform. However, near-term devices possess a range of possible imperfections that need to be accounted for during the tuning and operation of QD devices. One…